• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.134-134
• /
• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• Asian Journal of Innovation and Policy
• /
• v.9 no.2
• /
• pp.223-239
• /
• 2020

It is important for urban planners and policy makers to understand complex, diverse urban demands and social structure, but this is not easy due to lack of data that represents the dynamics of residents at micro-geographical level. This paper explores how to create population data at at a micro-level by allocating population data to building. It attempted to allocate population data stored in a grid layer (100 meters by 100 meters) into a building footprint layer that represents the appearance of physical buildings. For the allocation, this paper describes a systemic approach that classifies grid cells into five prototypical patterns based on the composition of residential building types in a grid cell. This approach enhances allocation accuracy by accommodating heterogeneity of urban space rather than relying on the assumption of uniform spatial homogeneity of populations within an aerial unit. Unlike the methods that disaggregate population data to the parcel, this approach is more applicable to Asian cities where large multifamily residential parcels are common. However, it should be noted that this paper does not demonstrate the validity of the allocated population since there is a lack of the actual data available to be compared with the current estimated population. In the case of water and electricity, the data is already attached to an individual address, and hence, it can be considered to the purpose of the validation for the allocation. By doing so, it will be possible to identify innovative methods that create a population distribution dataset representing the comprehensive and dynamic nature of the population at the micro geographical level.

• The KIPS Transactions:PartD
• /
• v.11D no.4
• /
• pp.835-844
• /
• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. Range queries, whose range can be window or circular, are the most essential query types in LBS. We need to distinguish completely contained cells from partially contained cells in those range queries. Also, it is necessary to consider temporal dimension to filter out qualifying objects correctly. In this paper, we adopt two-level index structures with fixed grid file structures in the second level, which are designed to minimize update operations. We propose a spatial ceil filtering method using VP filtering and a combined spatio-temporal filtering method using time gone concepts. Some experimental results are shown for various window queries and circular queries with different filtering combinations to show the performance tradeoffs of the proposed methods.

• Journal of Wetlands Research
• /
• v.13 no.1
• /
• pp.105-116
• /
• 2011

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, the exact relationship and the spatial variability analysis of hydrometeorological elements and characteristic factors is critical elements to reduce the uncertainty in rainfall -runoff model. In this study, radar rainfall grid resolution and grid resolution depending on the topographic factor in rainfall - runoff models were how to respond. In this study, semi-distribution of rainfall-runoff model using the model ModClark of Inje, Gangwon Naerin watershed was used as Gwangdeok RADAR data. The completed ModClark model was calibrated for use DEM of cell size of 30m, 150m, 250m, 350m was chosen for the application, and runoff simulated by the RADAR rainfall data of 500m, 1km, 2km, 5km, 10km from 14 to 17 on July, 2006. According to the resolution of each grid, in order to compare simulation results, the runoff hydrograph has been made and the runoff has also been simulated. As a result, it was highly runoff simulation if the cell size is DEM 30m~150m, RADAR rainfall 500m~2km for peak flow and runoff volume. In the statistical analysis results, if every DEM cell size are 500m and if RADAR rainfall cell size is 30m, relevance of model was higher. Result of sensitivity assessment, high index DEM give effect to result of distributed model. Recently, rainfall -runoff analysis is used lumped model to distributed model. So, this study is expected to make use of the efficiently decision criteria for configurated models.

• Journal of Environmental Impact Assessment
• /
• v.28 no.6
• /
• pp.556-567
• /
• 2019

As the number of skyscrapers in micro water grid units such as green building and smart building is increasing in the world, the green building certification system is being implemented to solve problems such as increased demand for water resources and energy. However, researches on the use of sustainable water resources like water reuse and water conservation through linkage and continuous use of water resources, while the power and energy sectors are actively conducting R&D projects in the green building certification system on the micro water grid level. Therefore, this paper analyzes the characteristics and limitations of the water resources sector for the continuous utilization of multiple water sources in the green building certification system, due to the inadequate consideration of sustainability. Then investigates whether various water resources such as constants, nature, and alternative water resources are continuously used in and out of the green building or smart building and complex in the micro water grid unit to suggest evaluation methods and performance evaluation standards.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.3
• /
• pp.12-36
• /
• 2023

Graph databases, which store different types of data and their relationships modeled as a graph, can be effective in managing and analyzing real estate spatial data linked by complex relationships. However, they are not widely used due to the limited spatial functionalities of graph databases. In this study, we propose a uniform grid-based real estate spatial data management approach using a graph database to respond to various real estate-related spatial questions. By analyzing the real estate community to identify relevant data and utilizing national point numbers as unit grids, we construct a graph schema that linking diverse real estate data, and create a test database. After building a test database, we tested basic topological relationships and spatial functions using the Jackpine benchmark, and further conducted query tests based on various scenarios to verify the appropriateness of the proposed method. The results show that the proposed method successfully executed 25 out of 29 spatial topological relationships and spatial functions, and achieved about 97% accuracy for the 25 functions and 15 scenarios. The significance of this study lies in proposing an efficient data integration method that can respond to real estate-related spatial questions, considering the limited spatial operation capabilities of graph databases. However, there are limitations such as the creation of incorrect spatial topological relationships due to the use of grid-based indexes and inefficiency of queries due to list comparisons, which need to be improved in follow-up studies.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.6
• /
• pp.890-898
• /
• 2022

Dispersion of suspended sediment, caused by coastal and marine development, is a key item in assessing marine environmental impact as it adversely affects marine life by increasing the level of turbidity and decreasing the amount of sunlight in seawater. However, its estimation has not been reliable because of the absence of a standard for the data measurement and divergent approaches to the impact assessment. In this study, we examined the estimation models from 58 Marine Environmental Impact Statements (MEISs, 2012-2014) to identify the gaps in the assessment and devise ways of improving the estimation. We developed four index items-grid system; unit load, particle size, and settling velocit-to evaluate their reliability in the estimation. The mean reliability score of each index was overall low-25 for grid system, 60 for unit load, 34 for particle size, and 17 for settling velocity. To ensure high reliability, it is important to develop a standard guideline that defines precise measurement of suspended sediment for unit load and settling velocity by particle size, followed by a grid system with compatible size for modelling. This can improve the estimation and thus underlie coherent impact assessment of suspended sediment dispersion on marine environment.

• Journal of radiological science and technology
• /
• v.41 no.6
• /
• pp.533-538
• /
• 2018

As the use of digital radiographic system has been expanded, there are some concerns an increase about in patient of radiation dose. Therefore, International Electro-technical Commission (IEC) has been proposed a standard foe exposure index (EI). In this study, the EI was measured on human chest model using computed radiography (CR). Radiation quality used RQA5 of IEC62494-1. After acquiring the chest anterior posterior image (Chest AP) by using the phantom, the EI was obtained by applying the system response. In this study, we have analyzed the images with the detector size (Full filed ROI) and the optimized image (Fit filed ROI). The EI increased proportionally with radiation dose increase. Due to the discrete increase in pixel value, the EI showed an exponential increase. The discrete increase in noise equivalent quanta (NEQ) resulted in a discrete increase in the EI. The EI of the two images used in this study increased with increasing NEQ but showed different increments. For the measurement of the EI, IEC standards must be followed. The EI should be used as an index to evaluate the image quality for quality control of X-ray image rather than as an indicator of exposure dose. When calculating the EI, the system response should be applied depending on whether or not the grid is used. The size of the field should be obtained by including only the necessary parts.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.2
• /
• pp.1-11
• /
• 2019

Remote sensing products have long been used to monitor and forecast natural disasters. Satellite-derived rainfall products are becoming more accurate as space and time resolution improve, and are widely used in areas where measurement is difficult because of the periodic accumulation of images in large areas. In the case of North Korea, there is a limit to the estimation of precipitation for unmeasured areas due to the limited accessibility and quality of statistical data. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) is global satellite-derived rainfall data of 0.05 degree grid resolution. It has been available since 1981 from USAID (U.S. Agency for International Development), NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration). This study evaluates the applicability of CHIRPS rainfall products for South Korea and North Korea by comparing CHIRPS data with ground observation data, and analyzing temporal and spatial drought trends using the Standardized Precipitation Index (SPI), a meteorological drought index available through CHIRPS. The results indicate that the data set performed well in assessing drought years (1994, 2000, 2015 and 2017). Overall, this study concludes that CHIRPS is a valuable tool for using data to estimate precipitation and drought monitoring in Korea.

• The Korean Journal of Financial Management
• /
• v.26 no.1
• /
• pp.165-188
• /
• 2009

This paper has suggested the methodology for the frontier portfolios and the optimal portfolio under the mean-VaR framework, not assuming the normal distribution and considering the investor's preferences for the higher moments of return distributions. It suggested the grid and rank approach which did not need an assumption about return distributions to find the frontier portfolios. And the optimal portfolio was selected using the utility function that considered the 3rd and the 4th moments. For the application of the methodology, weekly returns of the developed countries index, the emerging market index and the KOSPI index were used. After the frontier portfolios of the mean-variance framework and the mean-VaR framework were selected, the optimal portfolios of each framework were compared. This application compared not only the difference of the standard deviation but also the difference of the utility level and the certainty equivalent expressed by weekly expected returns. In order to verify statistical significances about the differences between the mean-VaR and the mean-variance, this paper presented the statistics which were obtained by the historical simulation method using the bootstrapping. The results showed that an investor under the mean-VaR framework had a tendency to select the optimal portfolio which has bigger standard deviation, comparing to an investor under the mean-variance framework. In addition, the more risk averse an investor is, the bigger utility level and certainty equivalent he achieves under the mean-VaR framework. However, the difference between the two frameworks were not significant in statistical as well as economic criterion.